README.md

metadata

base_model: openai/whisper-large-v3
datasets:
  - BembaSpeech
license: apache-2.0
metrics:
  - wer
tags:
  - generated_from_trainer
model-index:
  - name: whisper-large-v3-bem-fsv
    results:
      - task:
          type: automatic-speech-recognition
          name: Automatic Speech Recognition
        dataset:
          name: BembaSpeech bem
          type: BembaSpeech
          args: bem
        metrics:
          - type: wer
            value: 0.4033761652809272
            name: Wer
      - task:
          type: automatic-speech-recognition
          name: Automatic Speech Recognition
        dataset:
          name: BembaSpeech
          type: BembaSpeech
          config: en
          split: test
        metrics:
          - type: wer
            value: 47.3
            name: WER

whisper-large-v3-bem-fsv

This model is a fine-tuned version of openai/whisper-large-v3 on the BembaSpeech bem dataset. It achieves the following results on the evaluation set:

• Loss: 0.4783
• Wer: 0.4034

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 1.75e-05
• train_batch_size: 4
• eval_batch_size: 4
• seed: 42
• gradient_accumulation_steps: 6
• total_train_batch_size: 24
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 500
• num_epochs: 2.0
• mixed_precision_training: Native AMP

Training results

Framework versions

• Transformers 4.44.0
• Pytorch 2.4.0+cu121
• Datasets 2.21.0
• Tokenizers 0.19.1